DocumentCode
3316078
Title
Identification of IM Resistance Using Artificial Neural Network in Low Speed Region
Author
Sönmez, Murat ; Yakut, Mehmet
fYear
2007
fDate
3-6 Dec. 2007
Firstpage
437
Lastpage
442
Abstract
This paper presents a new method of estimation for the stator and rotor resistances of the induction motor for speed sensorless motor control drives, using artificial neural networks. The error between the motor quantity based on a neural network model and a voltage model is back propagated to adjust the weights of the neural network model for the stator resistance estimation. For the rotor resistance estimation, the error between the measured stator current and the estimated stator resistance using neural network is back propagated to adjust the weights of the neural network. The rotor speed is extracted from the induction motor state equations. The performance of the stator and rotor resistance estimators are investigated with the help of measured the stator voltage and current. Both resistances are estimated experimentally, using the proposed neural network in an induction motor drive.
Keywords
backpropagation; electric current measurement; electric machine analysis computing; induction motor drives; neural nets; voltage measurement; IM resistance identification; artificial neural network; back propagation; current measurement; induction motor; rotor resistance estimation; speed sensorless motor control drives; stator estimation; voltage measurement; Artificial neural networks; Current measurement; Electrical resistance measurement; Estimation error; Induction motors; Motor drives; Neural networks; Rotors; Stators; Voltage;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Sensors, Sensor Networks and Information, 2007. ISSNIP 2007. 3rd International Conference on
Conference_Location
Melbourne, Qld.
Print_ISBN
978-1-4244-1501-4
Electronic_ISBN
978-1-4244-1502-1
Type
conf
DOI
10.1109/ISSNIP.2007.4496883
Filename
4496883
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